1. Technical Field
The present invention relates generally to crash detection and damage mitigation systems for automotive vehicles, and more particularly to external airbag deployment in crash situations.
2. Background Art
Due to the current density of traffic on the roads, motor vehicle operators are flooded with information. Consequently, operating a motor vehicle is a complex procedure in which various situations occur in which the operator has limited, little, or no time to react or to manually engage safety measures.
Many previously known crash detection systems have incorporated crash detection algorithms based on sensed data. The application of remote sensing systems using radar, lidar, and vision-based technologies for object detection, tracking, alarm processing, and potential safety countermeasure activation is well known in the art.
Based on range and bearing information provided by radar, lidar or vision-based sensing systems and additional information obtained from the host vehicle sensors, various algorithms have been used to track the paths of host and target vehicles. Algorithms have also been incorporated to estimate the future position of obstacles or vehicles in the host vehicle path.
Some safety systems, such as front and side airbags, activate after physical contact occurs between two vehicles. A typical airbag deploys within approximately 70 ms. Both active and passive safety countermeasures can take advantage of pre-crash sensing. For example, a typical motorized retractable belt requires about 200 ms or more to reduce the slack in the belt system and pull the driver closer to the seat. Through accident prediction, additional time is generated for the deployment of active and passive countermeasures.
Currently, accident prediction algorithms are used primarily for collision warning and avoidance and therefore typically cover ranges up to a few hundred meters ahead of the host vehicle. However, in unavoidable collision situations, the range under consideration is substantially shorter. Therefore, damage minimization techniques must predict an unavoidable collision and deploy safety measures within a short time.
For pre-crash sensing, vehicle sensors need to not only detect possible threats but classify them as well. Classifications are often broken down into different target categories, such as: target vehicle type, wall, pole, and pedestrian.
For situations involving the target vehicle category, a classification scheme is patent pending for Ford Global Technologies to determine the direction and angle of the target vehicle and its type, e.g., frontal view of a car, side view of an SUV, and rear view of a large truck.
The limitations associated with current accident damage minimization techniques have made it apparent that a new technique to minimize collision damage is needed. The new technique should predict a target vehicle's position with respect to a host vehicle and should also provide a deployment decision tailored to the nature and time requirement of the countermeasure. The new technique should also reduce structural damage incurred by the host and target vehicles. The present invention is directed to these ends.